Magnetoencephalographic Mapping of Epileptic Spike Population Using Distributed Source Analysis: Comparison With Intracranial Electroencephalographic Spikes

Abstract

Introduction: This study evaluates magnetoencephalographic (MEG) spike population as compared with intracranial electroencephalographic (IEEG) spikes using a quantitative method based on distributed source analysis.

Methods: We retrospectively studied eight patients with medically intractable epilepsy who had an MEG and subsequent IEEG monitoring. Fifty MEG spikes were analyzed in each patient using minimum norm estimate. For individual spikes, each vertex in the source space was considered activated when its source amplitude at the peak latency was higher than a threshold, which was set at 50% of the maximum amplitude over all vertices. We mapped the total count of activation at each vertex. We also analyzed 50 IEEG spikes in the same manner over the intracranial electrodes and created the activation count map. The location of the electrodes was obtained in the MEG source space by coregistering postimplantation computed tomography to MRI. We estimated the MEG- and IEEG-active regions associated with the spike populations using the vertices/electrodes with a count over 25.

Results: The activation count maps of MEG spikes demonstrated the localization associated with the spike population by variable count values at each vertex. The MEG-active region overlapped with 65 to 85% of the IEEG-active region in our patient group.

Conclusions: Mapping the MEG spike population is valid for demonstrating the trend of spikes clustering in patients with epilepsy. In addition, comparison of MEG and IEEG spikes quantitatively may be informative for understanding their relationship.

Figure 1

Schematic representation of the MEG analysis. (A) Analysis of each individual spike. A source distribution map is obtained at the spike peak by using MNE (A-Left, B-Left). Source waveforms are extracted at all vertices (B-Middle) and each vertex is considered activated (count=1) or non-activated (count=0) by a threshold (A-Middle, Right). Thus, a map with count 1/0 is created for each spike (B-Right). (B) Analysis of spike population. A series of maps with count1/0 are created from each spike of the population (C-Left, Middle, Right). The total count at each vertex is mapped in the source space, creating an activation count map (D-Left). The vertices with count over 25 of 50 spikes are selected, and the vertices within 10mm of these vertices are estimated as the MEG-active region, which is the active region associated with the spike population (D-Middle, Right).

Figure 2

Schematic representation of the IEEG analysis. (A) Analysis of each individual spike. A map with the activated (count=1) and non-activated (count=0) electrodes is created for each spike (A-Left. Middle, Right) by using the same manner as shown on Fig. 1A, B. (B) Analysis of spike population. An activation count map is created (B-Left, Middle) from the spikes by using the same manner as shown in Fig. 1C, D-Left. The electrodes with count over 25 of 50 spikes are selected, and the vertices within 10mm of the vertices nearest to the center of these electrodes are estimated as the IEEG-active region, which is the active region associated with the spike population (B-Right).

Figure 3

MNE maps of a representative patient (patient 4). (Left) The maps demonstrate widespread (Left) and restricted (Right) source distribution for different individual spikes.

Figure 4

Maps of activation counts, MEG- and IEEG-active regions in a representative patient (patient 4). (A) An activation count map obtained from 50 MEG spikes (Left) and the estimated MEG-active region (Right). (B) An activation count map obtained from 50 IEEG spikes (Left) and the estimated IEEG-active region (Right).